import torch
from torch.autograd import Variable

"""This is a template for the model class."""

class Model1:
    def __init__(self, model_path):
        self.model = torch.load(model_path)
        self.model.eval()  # Set the model to evaluation mode

    def process_input(self, input_data):
        # Convert the input data to a PyTorch Variable
        processed_data = Variable(torch.FloatTensor(input_data))
        return processed_data

    def forward(self, input_data):
        processed_data = self.process_input(input_data)
        output_data = self.model(processed_data)
        return self.process_output(output_data)

    def process_output(self, output_data):
        # Convert the output data to a numpy array
        processed_data = output_data.data.numpy()
        return processed_data